Research On Path Planning Based On Lead Vehicle Historical Location Points And Trajectory Following Control Method

Nowadays,intelligent vehicles play an extremely important strategic role in solving traffic jams,traffic accidents and other problems.As an important part of the process of realizing vehicle intellectualization,path planning and trajectory following control method,is the necessary link of realizing intelligent driving.Therefore,the path planning and trajectory following control is deeply studied,mainly completed the following work:(1)A method of local path planning based on the historical track points of the lead car is studied.Through the interpretation of EyeQ output signal,a method of path generation consistent with its output trajectory description is designed.By recording and processing the historical trajectory points of the front car,the trajectory output that can be used by the lower control module is obtained,so that the vehicle can work due to the lack of track lines in the course of driving.The problems that can be rolled out have been solved.(2)A speed decision method of longitudinal adaptive cruise control is studied.The linear model predictive control method is used to obtain the optimal acceleration considered both the safe space and relative speed.The simulation analysis of the algorithm is carried out,and its effectiveness is verified.(3)A feedforward feedback transverse controller based on preview lateral error and predicted heading angle error is studied.A feedforward controller based on preview lateral error is established by considering vehicle dynamics and steady-state vehicle circle motion.A feedback controller based on predicted heading angle error is built by using heading angle prediction method,and a preview range adjuster is established by using fuzzy control method on velocity and road curvature.The simulation results show that the lateral controller can drive the car on curved road with variable curvature,and has a certain adaptability to the change of vehicle speed,and has a high tracking accuracy.(4)Considering the stability of vehicles on wet and slippery roads,a linear time-varying model predictive path following controller based on the linear two-degree-of-freedom vehicle dynamics model is established.The corresponding control constraints,physical limit constraints and dynamic constraints are added to the solution process of the controller to ensure vehicle driving stability.Compared with the unconstrained feed-back controller,the model predictive path following controller can better maintain vehicle stability under the condition of low road adhesion coefficient.(5)The virtual sensor in Carsim is used to acquire the vehicle information,and the corresponding trajectory planning module,longitudinal control module and lateral control module are built in Simulink to complete the simulation of the overall scheme.The simulation results show that the algorithm can enable the vehicle to follow the lead car on the road with variable curvature without relying on the road line information,and keep safe space with the lead car.